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Carbon Footprint Estimation in Road Construction:La Abundancia–Florencia Case Study
Marianela Espinoza 1, Noelia Campos 1, Rebekah Yang 2 , Hasan Ozer 2,José P. Aguiar-Moya 1,* , Alejandra Baldi 1 , Luis G. Loría-Salazar 1 and Imad L. Al-Qadi 2,3
1 National Laboratory of Materials and Structural Models, University of Costa Rica, San José 11501, Costa Rica;[email protected] (M.E.); [email protected] (N.C.);[email protected] (A.B.); [email protected] (L.G.L.-S.)
2 Transportation Engineering Solutions and Technologies, Inc., Champaign, IL 61822, USA;[email protected] (R.Y.); [email protected] (H.O.); [email protected] (I.L.A.-Q.)
3 Illinois Center for Transportation University of Illinois at Urbana, Champaign, IL 61822, USA* Correspondence: [email protected]; Tel.: +506-2511-2529
Received: 28 January 2019; Accepted: 14 March 2019; Published: 16 April 2019�����������������
Abstract: The environmental impact of road construction and rehabilitation can be associated with theincrease of greenhouse gas (GHG) emissions, which are highly related to climate change. Consequently,departments of transportation have recently focused on the development and implementation oftools to evaluate the performance of projects and minimize GHG emissions. An example is the use oflife cycle assessment (LCA) to analyze and quantify the environmental impact of a product, system,or process, from cradle to grave. In this regard, the present case study quantifies the carbon footprintassociated with the construction of the La Abundancia–Florencia highway, located in the province ofSan Carlos in Costa Rica. The analysis is also intended to generate consciousness both in the publicand private sectors on the environmental impacts of road construction. After an LCA study, it wasdetermined that the construction of the hot mix asphalt (HMA) layer generates a carbon footprintof 65.8 kg of CO2e per km of road. In addition, it was evident that HMA production generates thegreatest environmental impact, among all the considered LCA production and construction stages,with a GHG contribution of 38% to 39% from bitumen only. Consequently, special attention to HMAproduction is required in order to minimize GHG emissions.
Keywords: carbon footprint; GHG; life cycle analysis; emissions; road; asphalt mixtures
1. Introduction
Costa Rica has historically concerned itself with the environmental impact that is generated inthe development of different activities, from the extraction of raw materials to the final disposal offinished products, and their contribution to greenhouse gas (GHG) emissions. To exemplify suchconsiderations, the country is part of several international agreements, such as the United NationsFramework Convention on Climate Change (UNFCCC), signed on 13 June 1992 and in effect sinceJuly 1994 under Law No. 7414 [1]. It was also part of the 171 countries to sign the Paris Agreement,an international instrument that marks a milestone in the negotiations of the UNFCCC. More recently,the Carbon Neutral Program was signed, which aims to achieve carbon neutrality by the year 2100.
Also, it is important to note that in Costa Rica, one of the major sources of emissions is the energysector (46% of total emissions) and the vast majority is attributed to the transport sector [2]. Due to this,the country has approved 117 energy laws since the 1950s. However, most of this legislation focuseson hydrocarbons and hydroelectricity [3], leaving aside the road infrastructure sector, which is affectedby fuel consumption and the corresponding GHG emissions.
Sustainability 2019, 11, 2276; doi:10.3390/su11082276 www.mdpi.com/journal/sustainability
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In the past few decades, population growth in Costa Rica has generated a significant increasein the demand for goods and services. This also generates more demand on mobility and hence anincrease in traffic, which may accelerate pavement deterioration [4]. This has led to the need to havean efficient transport system, where in addition to promoting new non-motorized mobility alternativesand improving the quality of public transportation, it is very important for the system to have a roadinfrastructure in optimal condition. The sector where the road under study is located is an importantarea of agricultural production; therefore, in addition to the transport of people, there is a lot oftransport of goods by land. Therefore, it is appropriate to have a good road infrastructure with theobjective of satisfying the constant increases in demand. Furthermore, the selection of materials andprocesses that have low environmental footprints has gained popularity in recent years. Specifically,the evaluation of the environmental impact from road construction, rehabilitation, and operation hasbecome a national interest, due to the greenhouse gases (GHGs) generated during such activities.Furthermore, the reduction of the environmental impact related to the road sector has become aninternational concern. In this sense, a systematic approach that has emerged to assess the environmentalimpact of pavements is the life cycle assessment (LCA) method. The LCA is a technique that can beused to analyze and quantify the environmental impact of a product, system, or process [5]. In addition,it provides a comprehensive approach to assess the environmental burden by examining the inputsand outputs throughout the life cycle of the product, system, or process, from obtaining raw material tothe end of its useful life. In order to do so, a case study begins with an estimation of the partial carbonfootprint of the product, and then continues to an LCA study. In a similar manner, several InternationalOrganization for Standardization (ISO) standards are used to establish the principles, requirements,and guidelines to quantify and communicate the carbon footprint (ISO 14067 [6]), and to regulate theLCA analysis (ISO 14040, ISO 14044, ISO 14020, ISO 14024, and ISO 14025 [7–11]). The stages of LCAare shown in Figure 1.
1
Figure 1. Stages for the life cycle assessment (LCA) used in the is study.
It is important to emphasize that the use of the LCA has additional benefits, since it allowscharacterization of the environmental performance of the construction road projects. This generatesinformation that can be used by the construction companies to predict the performance of theirprojects and to evaluate the compliance with environmental requirements. Similarly, it allows theselection of optimal materials and construction processes, reducing the GHG emissions and permittinga more sustainable approach. As an example, the Illinois Tollway in the United States has usedan LCA tool, developed by the University of Illinois at Urbana Champaign and other consultingpartners, to characterize projects, to perform comparisons, and to measure progress in sustainableperformance [12]. Through a case study, Yang and Al-Qadi [13] developed a tool to implement aprobabilistic LCA to evaluate the environmental impact of airport pavement construction. The case
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study was the construction of runway 10R-28L at Chicago O’Hare International Airport. Anotherexample was implemented in Michigan, where LCA was applied to estimate the carbon footprintof highway construction projects: the research provided a tool (Project Emission Estimator) thatintegrates data from construction management software to assess historical GHG emissions fromhighway construction projects [14]. An Indian project also developed a computer program toolkit(Carbon Footprint Calculator) to quantify the carbon footprints of various pavement systems [15].
When comparing the results of other LCA studies, some differences can be detected, whichare presented in Table 1, where some similar studies made on pavement around the world aretabulated. These variations are mainly due to certain factors, such as the stages included in theanalysis (material extraction, construction, transportation, operation, and end of life), the analyzedmaterials (conventional asphalt, polymer modified asphalt, recycled asphalt), and the project length(km). In addition, the distances of transport of the material from the production plant to the site, andthe use of renewable energy can generate significant differences between projects. For example, CostaRica uses renewably energy to supply electricity, so it is justified that, although a large percentage(23%) of energy is required to operate the plant components, the GHGs of the plant components arevery small (1%).
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Table 1. Some LCA studies on road pavements published in recent years.
Project DescriptionAnalyzed Stages Analyzed Materials Total Emissions
CO2e (tons) ReferenceLocation Length (km)
UnitedStates
4.7 Material production, Transportation, and ConstructionC1. Bitumen, crushed aggregates 4064
[16]C2. Recycled material fly ash, and foundry sand 3255
Sweden 1 Construction, Maintenance, and End of lifeC1. Bitumen, aggregate 55.41
[17]C2. Asphalt, SBS polymer 47.23
UnitedStates
2.4 Construction, Use, Maintenance, Rehabilitation, and End of life
C1. Concrete 3872
[18]C2. Asphalt 6730
C3. Overlay with asphalt 5598
Australia 0.1 Raw material extraction, Construction, and Maintenance C1. Asphalt, concrete, and limestone 180.6 [19]C2. Reused crushed rock and recycled concrete rubble 170.7
Portugal 1 Extraction, Production, Transportation, and Construction
C1. Aggregates, bitumen, cement 121.86
[20]C2. Aggregates, bitumen, polymer modified 116.66
C3. Aggregates, bitumen 104.54
C4. Aggregates, recycled asphalt 100.59
Malaysia 99.6 to 103.0 Rehabilitation Cement, stone aggregate, quarry dust, and bitumen 3247 [21]
China 20 Mixture mixing, Transportation, Laying, Compacting, andCuring phase Aggregate, bitumen, Portland cement 0.052 [22]
Italy 8.5 Construction and Maintenance Aggregates, bitumen, cement 0.212 [23]
C* stands for Case and is numbered according to quantity of cases analyzed in the study. SBS is styrene–butadiene–styrene.
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In this sense, Butt et al. analyzed two case studies, comparing conventional asphalt and polymermodified asphalt [17]. They found that the asphalt mixture containing conventional unmodified binderreleased 55.41 tons of CO2e, and the modified mixture, 47.23 tons of CO2e [17]. A slight differenceis observed with respect to the results of the present study, which may be due to the fact that themaintenance and end of life stages were considered and the distances of material transport from theplant to the site were greater (50 km). Furthermore, it is worth noting that the modified asphalt withpolymer generated lower emissions than conventional asphalt, which coincides with the results of thisproject. Similarly, it occurred with the results obtained by Araújo et al. with emissions of 116 tons ofCO2e for the modified asphalt with polymer and 121 tons of CO2e emissions in the case of unmodifiedasphalt [20].
Furthermore, Biswas showed in his study the results of the quantification of the carbon footprint inthe construction of a road using virgin materials and recycled materials (cases 1 and 2) [19]. In this case,180 tons of CO2e and 170 tons of CO2e emissions were observed, respectively. However, the authorexplained that the maintenance operations over a lifetime of 100 years represented 79% of the totallife cycle of GHG emissions, because they included the transport of materials, excavation activities,leveling, and paving [19]. This may explain the difference in results with respect to those of the presentstudy, because the maintenance stage was not included in the analysis. Other studies that have recentlybeen published are shown in Table 1.
After recognizing the importance of accounting for the environmental impact associated withroad infrastructure, the National Laboratory of Materials and Structural Models of the University ofCosta Rica (LanammeUCR) formalized a research line on sustainability in 2011. This included theestablishment of the initiative called “Green Pavements” [23], which refers to a series of projects thatfocused on the use of waste materials in pavement structures and the reduction of energy required toproduce hot mix asphalt (HMA) mixtures. More recently, a specific project on sustainability began in2017, which seeks to promote its application in road infrastructure through a multi-criteria approach(environmental, economic, and social) to ensure efficient use of resources and optimize the conservationof the environment. For example, development of HMA mix designs including plastic componentsfrom recycled bottles, as well as other waste polymers, appears as a suitable option to dispose tons ofwaste materials [24–29].
In general, over the last decades Costa Rica has promoted the reduction of environmental impacts,something that has been branded at the international level as “Essential Costa Rica”, which seeks toengage the national business sector to ensure the values of excellence, sustainability, innovation, socialprogress, and Costa Rican origin. Hence, the initiative of the present study aims at promoting theapplication of tools, such as LCA, that guarantee compliance with responsible practices and providequality standards.
In this study, the construction of highway La Abundancia–Florencia, located in San Carlos (latitude10.3351, longitude −84.4545, National Route 35, Costa Rica), was selected as the case study. The projecthas a length of 7 km, is four lanes (2 in each direction), and has a pavement structure comprisedof: 300 mm of sub-base, 240 mm of cement treated base (CTB), 70 mm of HMA with neat asphalt,and 60 mm of polymer-modified HMA. Figure 2 shows a cross-sectional view of the roadway (the boxindicates the lanes that are within scope of work).
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In this sense, Butt et al. analyzed two case studies, comparing conventional asphalt and polymer modified asphalt [17]. They found that the asphalt mixture containing conventional unmodified binder released 55.41 tons of CO2e, and the modified mixture, 47.23 tons of CO2e [17]. A slight difference is observed with respect to the results of the present study, which may be due to the fact that the maintenance and end of life stages were considered and the distances of material transport from the plant to the site were greater (50 km). Furthermore, it is worth noting that the modified asphalt with polymer generated lower emissions than conventional asphalt, which coincides with the results of this project. Similarly, it occurred with the results obtained by Araújo et al. with emissions of 116 tons of CO2e for the modified asphalt with polymer and 121 tons of CO2e emissions in the case of unmodified asphalt [20].
Furthermore, Biswas showed in his study the results of the quantification of the carbon footprint in the construction of a road using virgin materials and recycled materials (cases 1 and 2) [19]. In this case, 180 tons of CO2e and 170 tons of CO2e emissions were observed, respectively. However, the author explained that the maintenance operations over a lifetime of 100 years represented 79% of the total life cycle of GHG emissions, because they included the transport of materials, excavation activities, leveling, and paving [19]. This may explain the difference in results with respect to those of the present study, because the maintenance stage was not included in the analysis. Other studies that have recently been published are shown in Table 1.
After recognizing the importance of accounting for the environmental impact associated with road infrastructure, the National Laboratory of Materials and Structural Models of the University of Costa Rica (LanammeUCR) formalized a research line on sustainability in 2011. This included the establishment of the initiative called “Green Pavements” [23], which refers to a series of projects that focused on the use of waste materials in pavement structures and the reduction of energy required to produce hot mix asphalt (HMA) mixtures. More recently, a specific project on sustainability began in 2017, which seeks to promote its application in road infrastructure through a multi-criteria approach (environmental, economic, and social) to ensure efficient use of resources and optimize the conservation of the environment. For example, development of HMA mix designs including plastic components from recycled bottles, as well as other waste polymers, appears as a suitable option to dispose tons of waste materials [24–29].
In general, over the last decades Costa Rica has promoted the reduction of environmental impacts, something that has been branded at the international level as “Essential Costa Rica”, which seeks to engage the national business sector to ensure the values of excellence, sustainability, innovation, social progress, and Costa Rican origin. Hence, the initiative of the present study aims at promoting the application of tools, such as LCA, that guarantee compliance with responsible practices and provide quality standards.
In this study, the construction of highway La Abundancia–Florencia, located in San Carlos (latitude 10.3351, longitude −84.4545, National Route 35, Costa Rica), was selected as the case study. The project has a length of 7 km, is four lanes (2 in each direction), and has a pavement structure comprised of: 300 mm of sub-base, 240 mm of cement treated base (CTB), 70 mm of HMA with neat asphalt, and 60 mm of polymer-modified HMA. Figure 2 shows a cross-sectional view of the roadway (the box indicates the lanes that are within scope of work).
Figure 2. Cross-sectional view of roadway.
The specific project information was obtained by means of questionnaires applied to the pavement engineers of the construction companies responsible for the project. The information that could not be
Figure 2. Cross-sectional view of roadway.
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The specific project information was obtained by means of questionnaires applied to the pavementengineers of the construction companies responsible for the project. The information that could not becollected or measured was obtained using the Ecoinvent 3.0 database, which is a globally recognizedLCI (life cycle inventory) database for a broad range of environmental studies.
The selection of the particular project as a case study was based on the importance of the corridor,and for being the first project in Costa Rica in which a modifying polymer was applied to the asphalticbinder. Furthermore, the project serves as a pilot plan for which the main objective is to quantify GHGemissions and to communicate to stakeholders (academia, construction companies, and the generalpublic) the environmental impact of road projects.
2. Materials and Methods
The procedure used in this study was based on the methodologies proposed in ISO 14067 standards“Greenhouse gases—Carbon footprint of products—Requirements and guidelines for quantificationand communication” and ISO 14040 “Environment management—Life cycle assessment—Principlesand framework”. Both standards propose four main steps for the analysis: goal and scope definition,lifecycle inventory analysis (LCI), life cycle impact assessment, and lifecycle interpretation (Figure 3).In the case of the analysis of carbon footprint of products (CFP), only climate change was considered.This change is just a variety of environmental impacts that can arise from the life cycle of a product,and in the case of LCA, several environmental impacts (depletion of resources, air, water, land,and ecosystems) are assessed throughout the analysis process.
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collected or measured was obtained using the Ecoinvent 3.0 database, which is a globally recognized LCI
(life cycle inventory) database for a broad range of environmental studies.
The selection of the particular project as a case study was based on the importance of the corridor,
and for being the first project in Costa Rica in which a modifying polymer was applied to the asphaltic
binder. Furthermore, the project serves as a pilot plan for which the main objective is to quantify GHG
emissions and to communicate to stakeholders (academia, construction companies, and the general
public) the environmental impact of road projects.
2. Materials and Methods
The procedure used in this study was based on the methodologies proposed in ISO 14067 standards
“Greenhouse gases—Carbon footprint of products—Requirements and guidelines for quantification and
communication” and ISO 14040 “Environment management—Life cycle assessment—Principles and
framework”. Both standards propose four main steps for the analysis: goal and scope definition, lifecycle
inventory analysis (LCI), life cycle impact assessment, and lifecycle interpretation (Figure 3). In the case of
the analysis of carbon footprint of products (CFP), only climate change was considered. This change is
just a variety of environmental impacts that can arise from the life cycle of a product, and in the case of
LCA, several environmental impacts (depletion of resources, air, water, land, and ecosystems) are
assessed throughout the analysis process.
Figure 3. Steps for the development of the analysis.
Goal and Scope Definition: the evaluated product corresponds to the HMA and polymer-modified
HMA mixtures for a new road, designed for a service life of 20 years without accounting for maintenance
interventions, taking into account that the tack coat was not evaluated on this occasion, because the
amount used (around 18 g/m2) was not significant, so the impact would be below cut-off limits. In
addition, the analyzed processes focused mainly on the extraction of raw material and construction of the
HMA layers. Being the first study of this type in the region, it focused specifically on these stages since the
information needed for the analysis could be collected or taken from databases, taking into account the
particular conditions of the project, during the process of execution of the work. Therefore, for the
subsequent stages (maintenance, waste disposals, end-of-life), there was no relevant information that
would allow the obtaining of a real evaluation. Consequently, this analysis can be classified as a partial
CFP since it did not consider the stages of operation, maintenance, use, and waste disposal of the project.
Figure 3. Steps for the development of the analysis.
Goal and Scope Definition: the evaluated product corresponds to the HMA andpolymer-modified HMA mixtures for a new road, designed for a service life of 20 years withoutaccounting for maintenance interventions, taking into account that the tack coat was not evaluated onthis occasion, because the amount used (around 18 g/m2) was not significant, so the impact wouldbe below cut-off limits. In addition, the analyzed processes focused mainly on the extraction ofraw material and construction of the HMA layers. Being the first study of this type in the region,it focused specifically on these stages since the information needed for the analysis could be collectedor taken from databases, taking into account the particular conditions of the project, during the
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process of execution of the work. Therefore, for the subsequent stages (maintenance, waste disposals,end-of-life), there was no relevant information that would allow the obtaining of a real evaluation.Consequently, this analysis can be classified as a partial CFP since it did not consider the stages ofoperation, maintenance, use, and waste disposal of the project. As per ISO 14067, a partial CFP isdefined as the “sum of greenhouse gas emissions and removals of one or more processes selectedfrom a system, expressed as CO2 equivalent (denoted here as CO2e), and based on the relevant stageswithin the life cycle” [3]. According to ISO 14067, it is necessary to define a functional unit to provide areference for which inputs and outputs are related. In the case of this study, the functional unit was onelane-km; thus the methodology was followed measuring the total impact of the GHGs in kg-CO2 perlane-km, responding to the fact that it would allow an easier comparison with other studies, since it isa functional unit of common use.
Life Cycle Inventory: the data for the analysis was collected by two sources. First, data wascollected by means of questionnaires distributed to the engineers/technicians of the company in chargeof the construction. The collected information was related to the practices, techniques, equipment,and type of energy used during the analysis period. Second, the information for the systems prior tothe construction process (i.e., extraction of aggregates, fuel processing) was obtained through databasesspecialized in the subject. The main database used for these processes was Ecoinvent 3.0. This toolwas developed by the Swiss Center for Life Cycle Inventories. Although it is true that a large part ofthe Ecoinvent database is applicable to Europe, specific primary data were collected for each projectand secondary data models were developed (for example, for petroleum fuels, electricity) to bettercharacterize data to Costa Rica. Finally, to integrate the information from the questionnaires withthat obtained from the database, the SimaPro 8.3.3 software that is specific to LCA was used forthe modeling. SimaPro is a commercial LCA software that integrates with the Ecoinvent databases,is user-friendly, and contains all the software features needed to model unit processes. For conductingthe study, each product required a separate evaluation process. The methodology for collectinginformation and processing the products considered for the analysis is summarized as follows:
(a) Petroleum products: when calculating the GHGs to produce the different petroleum products,a model developed by Yang et al. was used [30]. The evaluated impact included the extraction,transport, refinery, and transport processes to Puerto Moín, assuming that the product wastransported by tanks from the Gulf Coast in the United States to Puerto Moín in Costa Rica,a distance of 2640 km.
(b) Electric energy: the generation of electric power depends on the sources used to produce electricity.These sources can be coal, oil, wind, and solar energy. However, in Costa Rica, electric poweris renewable, using hydroelectric, geothermal, and wind power sources. Therefore, the GHGsemitted in Costa Rica related to energy production are among the lowest in the world [31].
(c) Asphalt: since two mix designs were used in the project, two types of asphalt were consideredat the time of the analysis. The first was modeled as an AC-30 (PG 64-22). For the second,it was modeled as a polymer-modified asphalt (PMA). In this case the asphalt was mixed with aterpolymer and polyphosphoric acid. As the exact composition of these additives is patented,a generic styrene–butadiene–styrene (SBS) commonly used in PMA was assumed and modeledbased on the Eurobitume life cycle inventory report [32]. It is also assumed that the SBS was 30%styrene and 70% butadiene and was mixed with the asphalt using an electric high shear stirrer.The PMA was classified as PG 76-22.
(d) Aggregates: the aggregates used were extracted from two riverbeds, one located 7 km and theother 15 km from the asphalt plant. The material was then transported and crushed (primaryand secondary crushers), and finally washed. For both HMA mix designs, the same aggregatesstockpiles were used: coarse (19 mm nominal maximum aggregate size (NMAS)), intermediate(16 mm NMAS), and fine aggregates. The production processes for the aggregates were modeledbased on the models for crushing and production in Ecoinvent 3.0. Each of the sizes of aggregatesused was analyzed separately, because the crushing and production was different for each
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case; due to this, the energy consumption of each product evaluated also varied. Therefore,an allocation procedure was used to distribute the total energy used in the system to each of theproducts, using the market value of the product supplied by the local producers. The allocationfactor is presented in Table 2 and represents the relative environmental impact of the product tothe average aggregate product produced in the facility.
(e) Asphalt plant: the production process in the asphalt plant was modeled using the informationobtained from the questionnaires and supplementary data from the database Ecoinvent 3.0.The asphalt plant operates with diesel oil for the drying and heating processes. Similar toaggregates, the Ecoinvent 3.0 global model for asphalt production was used to estimate electricityand fuel usage for non-dryer-related plant components (28% of total energy usage in plantoperations), which were then modeled with Costa Rican energy processes. The United StatesNational Asphalt Pavement Association (NAPA) model was used to estimate the energy requiredfor drying (78% of total energy), using a contractor survey to obtain the parameters for the NAPAmodel and the type of dryer fuel used, which required the mixing temperature and moisturecontent as inputs to the model [33]. An average temperature of 159 ◦C and a moisture content of5% were used as inputs in the analysis.
(f) Hauling: the raw materials were transported in trucks to the plant and from the plant to theconstruction site. The environmental impacts per ton-km for a class size greater than 32 tonswere determined. It should be noted that Costa Rica only complies with the EURO 1 standardrequirements at this time, but in this study, it was assumed that the truck complied with theEURO 3 standards, since the EURO emissions standards target NOx, CO, and other gases that donot significantly affect GHGs. Thus, an increased emissions standard should not directly affectthe GHGs. Furthermore, one-way trips were considered for hauling.
(g) Construction equipment: the specific equipment that operated in the construction of the analyzedsection was determined from the questionnaires. For each type of equipment, the respectiveefficiency (L/h), speed (km/h), and weight (ton) was identified. The equipment consistedof one asphalt paver, two vibratory steel wheel rollers, one pneumatic tire roller, and onepavement sweeper.
Table 2. Allocation Factors for Aggregate Production by Type.
Aggregate Type Allocation Factor
Large aggregate (76 mm) 1.49Base/sub-base aggregate 1.93
Coarse aggregate 2.38Intermediate aggregate 2.38
Fine aggregate 2.67
In addition to the aforementioned products, this study considered the stages of design andconstruction, which are detailed below.
i. Design stage: the production of materials and mixes required for the HMA layers in thepavement structure were considered. Due to this, the environmental impacts generated by theproduction process and transport to the asphalt plant were considered. The design of the HMAmixtures is shown in Table 3.
ii. Construction stage: in this stage the mobilization of equipment to the work site was considered,as well as their operation. In order to estimate the amount of fuel required by each equipment,the total operation time was estimated using the productivity rates defined in the NCHRPReport 744: Fuel usage factors in highway and bridge construction [34]. In addition to the fuelconsumption data (L/h) obtained for each equipment, the hours of use and the correspondingenvironmental impacts for the equipment were obtained.
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Table 3. Mix Design of Asphalt Concrete Layers.
Mix Design Hot MixAsphalt (HMA) Layer Category Item Design Amount
(Ton/Project)
Polymer-modified
Volumetric
Air voids 4.00% -Voids in mineral aggregate (VMA) 14.75% -
Bulk specific gravity (Gmb) 2.403 -Maximum theoretical specific gravity (Gmm) 2.499 -
Materials
Polymer-modified bitumen 5.10% 358Coarse aggregate 20.00% 1331
Intermediate aggregate 15.00% 998Fine aggregate 65.00% 4327
Unmodified
Volumetric
Air voids 4.00% -Voids in mineral aggregate (VMA) 14.72% -
Bulk specific gravity (Gmb) 2.397 -Maximum theoretical specific gravity (Gmm) 2.497 -
Materials
AC-30 5.55% 453Coarse aggregate 27.00% 2082
Intermediate aggregate 20.00% 1542Fine aggregate 53.00% 4086
3. Results and Discussion
In this CFP study, analyzing the La Abundancia–Florencia highway project, it was possible toevaluate the GHG emissions from the production and construction processes. The primary data (onprocesses, techniques, equipment, and fuel sources used) were obtained by means of questionnairesthat requested information from the project contractors and the administration. The secondary data(information which could not be measured in the project) were acquired from the Ecoinvent LCI 3.0database, and the application of LCA SimaPro 8.3.3.
The use of petroleum products (diesel, gasoline, and lubricants) was modeled first because theyare used in several processes for the production of the paving material, construction, transportation,and vehicular operation. It is highlighted that Costa Rica does not extract crude oil or refinedasphalt but imports them from other regions; since 2016 they have been imported from ten differentcountries, such as Venezuela, Panama, Belgium, Trinidad and Tobago, the United States, among others.The United States has five distinct Petroleum Administration for Defense Districts (PADD). In thisstudy we assumed that all products exported to Costa Rica came from PADD3 (Gulf Coast), becauseover the last five years, out of the five PADDs, PADD3 has consistently exported the greatest volume ofcrude oil and petroleum products internationally [35].
Other factors included in the modeling were electricity and energy sources for production. In thecase of Costa Rica, renewable energy is used to supply electricity, which positions the country as one ofthe countries with the lowest GHG emission from electric generation in the world.
The main components of the HMA mix, such as asphalt and aggregates, were also modeled.The GHG results for the polymer-modified asphalt were 11,369 kg of CO2e per lane-km with 16,572 kgof CO2e produced by the HMA plant, while the GHG results for the unmodified asphalt were 13,668 kgof CO2e per lane-km with 19,285 kg of CO2e generated by the HMA plant. The difference was associatedwith the structural design of the layers: the modified layer was thinner than the unmodified layer,and the optimum binder content for the modified HMA mixture was lower than that of the unmodifiedHMA mixture. In this sense, if the raw materials acquisition was lower, the GHG emissions would belower as well. Similarly, if the HMA mix design incorporated recycled materials, the emissions couldbe greatly reduced.
Table 4 shows the impact of GHG or global warming as estimated based on the previously detailedinformation. The GHG emissions are reported in kilograms of equivalent carbon dioxide (kg CO2e).
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Table 4. Design Stage Greenhouse Gas (GHG) Emissions Results.
Category Material GHG (kg CO2e/lane-km)
Polymer-modifiedHMA layer
Polymer-modified bitumen 11,369Coarse aggregate 313
Intermediate aggregate 234Fine aggregate 1109
HMA plant operation 16,572Polymer-modified asphalt (PMA) mix subtotal 29,596
Unmodified HMAlayer
Neat bitumen 13,668Coarse aggregate 489
Intermediate aggregate 362Fine aggregate 1047
HMA plant operations 19,285Conventional mix subtotal 34,851
Total Project subtotal 64,448
On the other hand, the total GHG emissions associated with the design and construction stages ofthe project under observation were estimated as well (Table 5). A summary of the GHG results for theproject per functional unit is shown in Figure 4.
Table 5. Total Project GHGs per Functional Unit.
Category Material GHG (kg CO2e/lane-km)
Design (Production)Polymer-modified HMA layer 29,596
Unmodified HMA layer 34,851Design subtotal 64,448
Construction Construction subtotal 1333
Total Project total 65,781
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Table 4. Design Stage Greenhouse Gas (GHG) Emissions Results.
Category Material GHG (kg CO2e/lane-km)
Polymer-modified HMA layer
Polymer-modified bitumen 11,369 Coarse aggregate 313
Intermediate aggregate 234 Fine aggregate 1109
HMA plant operation 16,572 Polymer-modified asphalt (PMA) mix subtotal 29,596
Unmodified HMA layer
Neat bitumen 13,668 Coarse aggregate 489
Intermediate aggregate 362 Fine aggregate 1047
HMA plant operations 19,285 Conventional mix subtotal 34,851
Total Project subtotal 64,448
On the other hand, the total GHG emissions associated with the design and construction stages of the project under observation were estimated as well (Table 5). A summary of the GHG results for the project per functional unit is shown in Figure 4.
Table 5. Total Project GHGs per Functional Unit.
Category Material GHG (kg CO2e/lane-km)
Design (Production) Polymer-modified HMA layer 29,596
Unmodified HMA layer 34,851 Design subtotal 64,448
Construction Construction subtotal 1333 Total Project total 65,781
Figure 4. GHG distribution for all processes in road project by percentage.
On the other hand, the aggregates that were used in the design of the two HMA mixtures (with and without polymer) were blended from stockpiles with nominal maximum aggregate size (NMAS) of 19 mm (coarse aggregate), 16 mm (intermediate), and fines. The aggregate materials were modeled based on the processes for crushed gravel production in Ecoinvent 3.0. The activities included extraction, processing, and transportation. To customize the unit processes, the electricity and diesel from the default
Construction 2%
Asphalt Layer53%
PMB Asphalt Layer45%
Figure 4. GHG distribution for all processes in road project by percentage.
On the other hand, the aggregates that were used in the design of the two HMA mixtures(with and without polymer) were blended from stockpiles with nominal maximum aggregate size(NMAS) of 19 mm (coarse aggregate), 16 mm (intermediate), and fines. The aggregate materials weremodeled based on the processes for crushed gravel production in Ecoinvent 3.0. The activities includedextraction, processing, and transportation. To customize the unit processes, the electricity and dieselfrom the default Ecoinvent 3.0 process were replaced with corresponding regional upstream processes.Likewise, it is important to note that each size may use unique amount of energy to be produced due
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to different crushing and processing requirements. This is an example of a multiple output process,where raw materials are inputted into a system, processed, and then outputted as various products.
In the case of the HMA plant, the amount of energy was estimated based on an energy modelfrom NAPA that uses the mixing temperature and moisture content as inputs [36]. It was observedthat the percentage of energy to operate the plant was very small (1%), compared to the typicalpercentage (23%). This was due to the use of renewable energy to generate electricity. To estimate theenvironmental impacts generated by each equipment during the on-site construction process, the fuelconsumption and the hours corresponding to each individual equipment were quantified.
Finally, the results of the evaluation showed that the construction of the HMA mix layer generateda carbon footprint of 65.8 kg of CO2e per lane-km. Of this amount, 2% was contributed by theconstruction of the roadway, while the remaining amount was contributed by the production processesrequired to obtain the materials needed for the roadway. The HMA plant operations contributedthe largest portion of GHGs (approximately 55%), while asphalt production contributed the secondlargest (38–39%). On the other hand, transportation represented a smaller portion with a 5–6% GHGcontribution. These results show that the production stage is the one that generates the greatest impact.For this reason, special attention must be given to determine possible approaches for GHG reductions.
When evaluating the results obtained with the international studies presented in Table 1, the resultsare significantly lower in most cases. However, by studying the methodologies that were used in thesestudies, it is possible to notice that the inventory analysis, the databases, and the software used inmodeling vary from one to the other, so it is not possible to make a real comparison of one with theother. Considering the above and also taking into account the particular situation of Costa Rica to haverenewable energy sources, it is possible to explain the differences found in the results of this analysiswith those that have been made around the world.
4. Conclusions
As part of the project, it was possible to quantify the GHG emissions from the construction projectof the La Abundancia–Florencia highway. In summary, the following data were obtained:
• The production and construction stages of the HMA layers generated a carbon footprint of65.781 kg of CO2e per lane-km.
• The production stage of polymer-modified HMA layer presented a contribution of 29.596 kg ofCO2e per lane-km, while the unmodified HMA layer contributed 34.851 kg of CO2e per lane-km.The unmodified HMA layer was thicker and used more asphalt content.
• Aggregate production contributed approximately 6% of total GHGs, which was similar to thetransport contribution (close to 6%).
• Considering production and construction stages only, the production stage contributedapproximately 98% of the total GHGs in this project, while the construction stage contributedonly 2% of the total GHGs.
Based on the results of the case study, the following conclusions and recommendations arise:
• The percentage of energy required to operate the components of the HMA plant is small (1%).This is because Costa Rica uses renewable energy to generate electricity. Therefore, GHG emissionsdue to electricity generation (kg of CO2e per lane-km) in Costa Rica are low.
• It is recommended to increase the efficiency of asphalt mixing equipment and techniques ofconstruction. The use of raw materials with lower emissions (e.g., Recycled Asphalt PavementRAP) can result in reducing energy use and corresponding emissions.
Finally, several recommendations can be drawn from this study, in order to reduce GHG emissions.For example, since the production stage is the one with the higher carbon footprint, there are severalpoints that can be improved to make the process more efficient, such as to define the most efficientroute for material transportation, to check the conditions of the trucks to ensure that no additional
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gasoline is required, and so on. Given the fact that these recommendations seem simple, the authorsconsider that a deeper analysis must be performed to find better ways to reduce the carbon footprintrelated to pavement road construction.
Author Contributions: Conceptualization, R.Y., H.O., M.E., N.C., and A.B.; methodology, I.L.A.-Q., R.Y., and H.O.;software, I.Q.; validation, R.Y., H.O., and I.L.A.-Q.; formal analysis, R.Y., H.O., and I.L.A.-Q.; investigation, M.E.and N.C., data curation, R.Y. and H.O.; writing—original draft preparation, M.E. and N.C.; writing—review andediting, A.B. and J.P.A.-M.; supervision, A.B., J.P.A.-M., L.G.L.-S., and I.L.A.-Q.
Funding: This research received no external funding.
Acknowledgments: The present study is based on the results obtained during the analysis carried out by TEST,Inc. Special thanks extend to the companies Constructora Herrera and Eurofinsa for the information provided tocarry out the study.
Conflicts of Interest: The authors declare no conflict of interest.
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